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RishuD7/Llama3.1_question_answer_model_wo_gen
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metadata
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
  - trl
  - sft
  - generated_from_trainer
model-index:
  - name: models
    results: []
library_name: peft

models

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2091

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

The following bitsandbytes quantization config was used during training:

  • quant_method: bitsandbytes
  • _load_in_8bit: True
  • _load_in_4bit: False
  • llm_int8_threshold: 6.0
  • llm_int8_skip_modules: None
  • llm_int8_enable_fp32_cpu_offload: False
  • llm_int8_has_fp16_weight: False
  • bnb_4bit_quant_type: fp4
  • bnb_4bit_use_double_quant: False
  • bnb_4bit_compute_dtype: float32
  • bnb_4bit_quant_storage: uint8
  • load_in_4bit: False
  • load_in_8bit: True

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
0.1235 0.9991 583 0.1561
0.0837 2.0 1167 0.1912
0.0693 2.9974 1749 0.2091

Framework versions

  • PEFT 0.4.0
  • Transformers 4.43.3
  • Pytorch 2.3.1+cu121
  • Datasets 2.13.0
  • Tokenizers 0.19.1